Position: Biostatistics / Data Science Lead (Can be remote)

If your skills, experience, and qualifications match those in this job overview, do not delay your application. Overview: Our client seeking a hands-on Biostatistics/Data Science leader to drive the design and implementation of scalable, compliant, and efficient statistical workflows supporting Gilead’s drug development programs. This role combines technical excellence in R and data engineering with leadership in cross-functional collaboration, reproducibility, and innovation within regulated environments. Key Responsibilities: Lead the development of R-based statistical tools , pipelines, and reproducible workflows to support clinical trial analysis and reporting. Collaborate with statisticians to translate complex methodologies into robust, validated R code for simulations, adaptive designs, and advanced analyses. Oversee R package development , GitHub workflows, and CI/CD pipelines, ensuring code integrity, documentation, and compliance. Define solution architectures integrating open-source tools and cloud-based infrastructures for large-scale, compliant data management. Partner with IT, data engineering, and business teams to streamline processes, enhance automation, and maintain data governance standards. Guide standardization and best practices for code development, validation, and regulatory readiness. Provide technical leadership and mentorship, managing timelines, deliverables, and quality expectations. Qualifications: PhD in Statistics, Biostatistics, Computer Science, or related field with 5 + years of experience (MS with 10+, BS with 12+). Deep expertise in R programming , R package development, and statistical implementation in clinical trials. Proven experience with GitHub version control , CI/CD, and collaborative coding workflows. Strong background in data engineering, automation, and reproducibility in a regulated (pharma/life sciences) environment. Familiarity with Pharmaverse packages and open-source software development practices. Excellent problem-solving, project management, and communication skills. Preferred: Experience with AWS/cloud data pipelines , distributed computing, and additional programming languages (Python, SQL). Demonstrated ability to bridge between statisticians, data scientists, and engineers.